Skip to content

Commit

Permalink
fix ref in readme & add orfmine image
Browse files Browse the repository at this point in the history
  • Loading branch information
nchenche committed Nov 13, 2022
1 parent 51061e8 commit 3818adb
Show file tree
Hide file tree
Showing 3 changed files with 51 additions and 27 deletions.
23 changes: 12 additions & 11 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,7 @@ all Open Reading Frames (ORFs) of a genome (including coding and noncoding seque
#### Built with
- python 3.6
- miniconda 3
- pyHCA <sup><a href="#references">1</a></sup>
- pyHCA <sup><a href="#references">3</a></sup>
- R
- bash
- Docker
Expand All @@ -26,8 +26,8 @@ All programs and dependencies are listed [here](docs/dependencies.md).
### Prerequisites

- [Docker](https://docs.docker.com/engine/install/) or [Singularity](https://singularity-tutorial.github.io/01-installation/)
- [IUPred](https://iupred2a.elte.hu/download_new) <sup><a href="#references">2, 3, 4</a></sup> (optional)
- [Tango](http://tango.crg.es) <sup><a href="#references">5, 6, 7</a></sup> (optional)
- [IUPred](https://iupred2a.elte.hu/download_new) <sup><a href="#references">4, 5, 6</a></sup> (optional)
- [Tango](http://tango.crg.es) <sup><a href="#references">7, 8, 9</a></sup> (optional)


### Installation
Expand Down Expand Up @@ -120,11 +120,12 @@ The ORFmine project is under the MIT licence. Please check [here](LICENSE.md) fo


## References

1. Bitard-Feildel, T. & Callebaut, I. HCAtk and pyHCA: A Toolkit and Python API for the Hydrophobic Cluster Analysis of Protein Sequences. bioRxiv 249995 (2018).
2. Dosztanyi, Z., Csizmok, V., Tompa, P. & Simon, I. The pairwise energy content estimated from amino acid composition discriminates between folded and intrinsically unstructured proteins. Journal of molecular biology 347, 827–839 (2005).
3. Dosztányi, Z. Prediction of protein disorder based on IUPred. Protein Science 27, 331– 340 (2018).
4. Mészáros, B., Erdős, G. & Dosztányi, Z. IUPred2A: context-dependent prediction of protein disorder as a function of redox state and protein binding. Nucleic acids research 46, W329–W337 (2018).
5. Fernandez-Escamilla, A.-M., Rousseau, F., Schymkowitz, J. & Serrano, L. Prediction of sequence-dependent and mutational effects on the aggregation of peptides and proteins. Nature biotechnology 22, 1302–1306 (2004).
6. Linding, R., Schymkowitz, J., Rousseau, F., Diella, F. & Serrano, L. A comparative study of the relationship between protein structure and β-aggregation in globular and intrinsically disordered proteins. Journal of molecular biology 342, 345–353 (2004).
7. Rousseau, F., Schymkowitz, J. & Serrano, L. Protein aggregation and amyloidosis: confusion of the kinds? Current opinion in structural biology 16, 118–126 (2006).
1. Papadopoulos, C., Chevrollier, N., Lopes, A. Exploring the peptide potential of genomes. Meth. Mol. Biol. (2022).
2. Papadopoulos, C., Arbes, H., Chevrollier, N., Blanchet, S., Cornu, D., Roginski, P., Rabier, C., Atia, S., Lespinet, O., Namy, O., Lopes, A. (submitted).
3. Bitard-Feildel, T. & Callebaut, I. HCAtk and pyHCA: A Toolkit and Python API for the Hydrophobic Cluster Analysis of Protein Sequences. bioRxiv 249995 (2018).
4. Dosztanyi, Z., Csizmok, V., Tompa, P. & Simon, I. The pairwise energy content estimated from amino acid composition discriminates between folded and intrinsically unstructured proteins. Journal of molecular biology 347, 827–839 (2005).
5. Dosztányi, Z. Prediction of protein disorder based on IUPred. Protein Science 27, 331– 340 (2018).
6. Mészáros, B., Erdős, G. & Dosztányi, Z. IUPred2A: context-dependent prediction of protein disorder as a function of redox state and protein binding. Nucleic acids research 46, W329–W337 (2018).
7. Fernandez-Escamilla, A.-M., Rousseau, F., Schymkowitz, J. & Serrano, L. Prediction of sequence-dependent and mutational effects on the aggregation of peptides and proteins. Nature biotechnology 22, 1302–1306 (2004).
8. Linding, R., Schymkowitz, J., Rousseau, F., Diella, F. & Serrano, L. A comparative study of the relationship between protein structure and β-aggregation in globular and intrinsically disordered proteins. Journal of molecular biology 342, 345–353 (2004).
9. Rousseau, F., Schymkowitz, J. & Serrano, L. Protein aggregation and amyloidosis: confusion of the kinds? Current opinion in structural biology 16, 118–126 (2006).
10 changes: 10 additions & 0 deletions docs/css/extra.css
Original file line number Diff line number Diff line change
Expand Up @@ -46,3 +46,13 @@

border-top: 6px solid black;
}

#img-orfmine {
padding: 2px;
margin-top: 3rem;
margin-bottom: 6rem;
}

.img-index {
margin-top: 3rem;
}
45 changes: 29 additions & 16 deletions docs/index.md
Original file line number Diff line number Diff line change
@@ -1,8 +1,8 @@
<div style="text-align:center;">
<img src="./img/icons/Logo_ORFmine.png" width="70%"/>
<div style="margin-top: 5px; margin-bottom: 5px;">
Chris Papadopoulos<sup>1</sup>, Nicolas Chevrollier<sup>2</sup>, Hugo Arbes<sup>1</sup>, Anne Lopes<sup>1</sup>
</div>
<img src="./img/icons/Logo_ORFmine.png" width="70%"/>
<div style="margin-top: 5px; margin-bottom: 5px;">
Chris Papadopoulos<sup>1</sup>, Nicolas Chevrollier<sup>2</sup>, Hugo Arbes<sup>1</sup>, Anne Lopes<sup>1</sup>
</div>
</div>

<div type="button" class="collapsible"><span class="arrow-down"></span>Affiliations</div>
Expand All @@ -13,7 +13,6 @@ Chris Papadopoulos<sup>1</sup>, Nicolas Chevrollier<sup>2</sup>, Hugo Arbes<sup>
<a href=mailto:[email protected]>[email protected]</a>,
<a href=mailto:[email protected]>[email protected]</a>.


</div>
<div style="margin-top: 6px;">
<sup>2</sup> Independent bio-informatician, Paris, France, <a href=mailto:[email protected]>[email protected]</a>.
Expand All @@ -35,13 +34,17 @@ ORFmine[1][2] is an open-source package that aims at extracting, annotating,
and characterizing the sequence and structural properties of
all Open Reading Frames (ORFs) of a genome (including coding and
noncoding sequences) along with their translation activity. ORFmine consists of several independent programs,
<b>ORFtrack</b>, <b>ORFold</b>, <b>ORFribo</b>, and <b>ORFdate</b>, that can be used together or independently
[**ORFtrack**](#anchor-orftrack), [**ORFold**](#anchor-orfold), [**ORFribo**](#anchor-orfribo), and [**ORFdate**](#anchor-orfdate), that can be used together or independently
(see [here](./orfmine_quickstart.md) for an example of
application).

<div id="img-orfmine" style="text-align:center;">
<img src="./img/icons/ORFmine.png" width="100%"/>
</div>


<br>
<div class="img-index" >
<a name="anchor-orftrack"></a>
</div>
[ ![](./img/icons/Logo_ORFtrack.png){ width=30% }](./orftrack_description.md) <br>

ORFtrack searches for all possible ORFs longer than 60 nucleotides in the six frames of an input
Expand All @@ -53,8 +56,12 @@ that can be directly uploaded on a genome viewer for a visual inspection.
In addition, their amino acid and/or nucleotide sequences can be extracted
in a FASTA file (for more details, see the complete
documentation of ORFtrack).

<br>

<div class="img-index" >
<a name="anchor-orfold"></a>
</div>

[![](./img/icons/Logo_ORFold.png){ width=30% }](./Objective_orfold.md) <br>

ORFold predicts the fold potential and the disorder and aggregation
Expand All @@ -70,23 +77,29 @@ respectively, thereby enabling the manual inspection of these
properties along a genome in a genome viewer
(for more details, see the complete
documentation of ORFold).
<br>

<div class="img-index">
<a name="anchor-orfribo"></a>
</div>

<br>
<br>
[![](./img/icons/Logo_ORFribo.png){ width=30% }](./Objective_orfold.md) <br>
[![](./img/icons/Logo_ORFribo.png){ width=30% }](./orfribo_objectives.md) <br>

ORFribo probes the translation activity of a set of ORFs of a genome based on Ribosome Profilng data (Ribo-Seq). ORFribo is very flexible and handles any type of ORFs once annotated in a GFF file (e.g. coding sequences, alternative ORFs (i.e., noncoding ORFs located in the alternative frames of CDSs) or intergenic ORFs). ORFribo has no a priori and does not predict any ORF status (translated or not for instance), but rather calculates for each ORF, the counts of reads that map on it along with the frame they are associated with (i.e., the frame of the ORF, or its two alternative frames), thereby providing information that can be indicative on the specificity of the translation of the ORF. The raw information is provided in a text table very easy to parse so that, the user is free to set its own thresholds (number of reads, specificity of translation (i.e. number of reads that are in the frame of the ORF)) to classify ORFs based on their translation signals and/or extract interesting candidates. In order to increase the read coverage of noncoding regions, expected to be low because they are usually associated with lower expression when expressed, ORFribo enables one to pool multiple Ribo-Seq datasets. Reads of good quality (quality thresholds are customizable by the user) of all datasets are thus merged together and the resulting signal is analyzed as a whole and provided as a single output table. The user is free to combine different datasets as he/she whishes (experiments performed in specific conditions, tissues etc).
<br>

<div class="img-index">
<a name="anchor-orfdate"></a>
</div>

<br>
<br>
[![](./img/icons/Logo_ORFdate.png){ width=30% }](./Objective_orfold.md) <br>
[![](./img/icons/Logo_ORFdate.png){ width=30% }](./orfdate_objectives.md) <br>

ORFdate estimates the evolutionary age (in Mya) of a set of ORFs of a genome (coding or noncoding ORFs) based on phylostratigraphy.
<br>
<br>
<br>


<br>

#### References

Expand Down

0 comments on commit 3818adb

Please sign in to comment.